Social Navigation

14 papers with code • 0 benchmarks • 1 datasets

This task studies how to navigate robot(s) among humans in a safe and socially acceptable way.

Libraries

Use these libraries to find Social Navigation models and implementations

Datasets


Most implemented papers

Habitat 3.0: A Co-Habitat for Humans, Avatars and Robots

facebookresearch/habitat-sim 19 Oct 2023

We present Habitat 3. 0: a simulation platform for studying collaborative human-robot tasks in home environments.

Robot Navigation in Constrained Pedestrian Environments using Reinforcement Learning

StanfordVL/iGibsonChallenge2021 16 Oct 2020

Navigating fluently around pedestrians is a necessary capability for mobile robots deployed in human environments, such as buildings and homes.

Decentralized Structural-RNN for Robot Crowd Navigation with Deep Reinforcement Learning

Shuijing725/CrowdNav_DSRNN 9 Nov 2020

Safe and efficient navigation through human crowds is an essential capability for mobile robots.

Intention Aware Robot Crowd Navigation with Attention-Based Interaction Graph

Shuijing725/CrowdNav_Prediction_AttnGraph 3 Mar 2022

We study the problem of safe and intention-aware robot navigation in dense and interactive crowds.

Social and Scene-Aware Trajectory Prediction in Crowded Spaces

Oghma/sns-lstm 19 Sep 2019

Mimicking human ability to forecast future positions or interpret complex interactions in urban scenarios, such as streets, shopping malls or squares, is essential to develop socially compliant robots or self-driving cars.

Social Navigation with Human Empowerment driven Deep Reinforcement Learning

tessavdheiden/SCR 18 Mar 2020

In contrast to self-empowerment, a robot employing our approach strives for the empowerment of people in its environment, so they are not disturbed by the robot's presence and motion.

Visual Navigation Among Humans with Optimal Control as a Supervisor

vtolani95/HumANav-Release 20 Mar 2020

Videos describing our approach and experiments, as well as a demo of HumANav are available on the project website.

SoLo T-DIRL: Socially-Aware Dynamic Local Planner based on Trajectory-Ranked Deep Inverse Reinforcement Learning

umich-curly/fetch_irl 16 Sep 2022

This work proposes a new framework for a socially-aware dynamic local planner in crowded environments by building on the recently proposed Trajectory-ranked Maximum Entropy Deep Inverse Reinforcement Learning (T-MEDIRL).

SOCIALGYM 2.0: Simulator for Multi-Agent Social Robot Navigation in Shared Human Spaces

ut-amrl/social_gym 9 Mar 2023

We present SocialGym 2, a multi-agent navigation simulator for social robot research.

SocNavGym: A Reinforcement Learning Gym for Social Navigation

gnns4hri/socnavgym 27 Apr 2023

We propose SocNavGym, an advanced simulation environment for social navigation that can generate a wide variety of social navigation scenarios and facilitates the development of intelligent social agents.